Application of computational tools for experimental data analysis of homogeneous catalytic systems in the synthesis of cyclic carbonates

Cycloaddition of CO2 to epoxides is considered to be a promising atom-efficient process for converting of the CO2 emissions to the valuable products. The present analytical review is dedicated to computational multivariance analysis of the published experimental data for homogeneously catalyzed reactions. In the vast majority of cases the catalytic system includes metal catalyst and cationic co-catalyst. Comprehensive data analysis implying AI tools revealed that the published data are highly noisy due to the prevailing role of the co-catalyst in catalysis. However, several experimental trends on the catalyst activity to structure relationship were formulated, the most active systems were highlighted and the possible directions of the further development were suggested.